Performance 快速查找图像中最近的非黑色像素
我有一张2D图像,随机地、稀疏地散布着像素。Performance 快速查找图像中最近的非黑色像素,performance,graphics,2d,pixel,Performance,Graphics,2d,Pixel,我有一张2D图像,随机地、稀疏地散布着像素。 给定图像上的一个点,我需要找到与背景色(黑色)以外的最近像素的距离。 最快的方法是什么 我能想到的唯一方法是为像素构建kd树。但我真的希望避免如此昂贵的预处理。而且,kd树似乎给了我比我需要的更多。我只需要距离的东西,我不在乎这是什么东西 搜索“最近邻搜索”,谷歌的前两个链接应该对你有所帮助 如果你只为每张图像做1个像素,我认为你最好的选择就是线性搜索,每次向外搜索1个像素宽的框。如果你的搜索框是正方形的,你就不能得到你找到的第一个点。你必须小心是的
给定图像上的一个点,我需要找到与背景色(黑色)以外的最近像素的距离。
最快的方法是什么 我能想到的唯一方法是为像素构建kd树。但我真的希望避免如此昂贵的预处理。而且,kd树似乎给了我比我需要的更多。我只需要距离的东西,我不在乎这是什么东西 搜索“最近邻搜索”,谷歌的前两个链接应该对你有所帮助
如果你只为每张图像做1个像素,我认为你最好的选择就是线性搜索,每次向外搜索1个像素宽的框。如果你的搜索框是正方形的,你就不能得到你找到的第一个点。你必须小心是的,最近邻搜索很好,但不能保证你会找到“最近的”。每次向外移动一个像素将产生一个正方形搜索-对角线将比水平/垂直方向更远。如果这很重要,您需要验证-继续展开,直到绝对水平距离大于“找到的”像素,然后计算所定位的所有非黑色像素上的距离。您没有指定要如何测量距离。我将假设L1(直线),因为它更容易;可能这些想法可以修改为L2(欧几里德) 如果只对相对较少的像素执行此操作,则只需从源像素向外搜索螺旋,直到找到非黑色像素 如果你对很多/所有的像素都这样做,那么这样做如何:构建一个图像大小的二维数组,每个单元格存储到最近的非黑色像素的距离(如果需要,还存储该像素的坐标)。进行四次扫线:从左到右、从右到左、从下到上和从上到下。考虑左右扫掠;扫描时,保留一个一维列,其中包含在每行中看到的最后一个非黑色像素,并用到该像素的距离和/或坐标标记二维阵列中的每个单元。O(n^2)
或者,k-d树是过度杀戮;你可以用四叉树。只比我的行扫描代码难一点,内存多一点(但不到两倍),可能更快 正如派罗所说,搜索从原点一次移出一个像素的正方形的周长(即一次增加两个像素的宽度和高度)。当点击非黑色像素时,计算距离(这是第一次昂贵的计算),然后继续向外搜索,直到框的宽度是到第一个找到点的距离的两倍(超出此范围的任何点都不可能比原始找到的像素更近)。保存在该零件中找到的所有非黑点,然后计算它们之间的距离,查看它们是否比原始点更近 在理想的查找中,您只需进行一次昂贵的距离计算 更新:因为您在这里计算像素到像素的距离(而不是任意精度的浮点位置),所以您可以通过使用预先计算的查找表(仅一个按宽度排列的高度)将距离作为x和y的函数,大大加快此算法的速度。一个100x100阵列基本上需要40K内存,并在原点周围覆盖200x200平方米,还可以省去为找到的每个彩色像素进行昂贵的距离计算(无论是毕达哥拉斯还是矩阵代数)的成本。这个数组甚至可以预先计算并作为资源嵌入到你的应用程序中,以节省你的初始计算时间(这可能是严重的过度使用) 更新2:还有一些方法可以优化搜索方形周长。您的搜索应该从与轴相交的四个点开始,并一次向拐角移动一个像素(您有8个移动的搜索点,这很容易使这一点变得更麻烦,具体取决于应用程序的要求)。一旦您找到一个彩色像素,就不需要继续朝向角点,因为其余的点都离原点更远 在第一个找到的像素之后,可以使用查找表进一步将所需的附加搜索区域限制到最小值,以确保每个搜索点都比找到的点更近(再次从轴开始,并在达到距离限制时停止)。如果您必须在飞行中计算每个距离,那么第二个优化可能会非常昂贵
如果最近的像素在200x200框内(或任何适合您的数据的大小),您将只在像素限定的圆内搜索,只进行查找和比较。我将为每个像素创建一个简单的查找表,预先计算到最近非黑色像素的距离,并将该值存储在与相应像素相同的偏移量中。当然,这样你需要更多的内存。就我个人而言,我会忽略MusiGenesis关于查找表的建议 计算像素之间的距离并不昂贵,特别是对于这个初始测试,您不需要实际距离,因此不需要取平方根。您可以使用距离^2,即:
r^2 = dx^2 + dy^2
此外,如果一次向外移动一个像素,请记住:
(n + 1)^2 = n^2 + 2n + 1
或者,如果nx是当前值,而ox是上一个值:
nx^2 = ox^2 + 2ox + 1
= ox^2 + 2(nx - 1) + 1
= ox^2 + 2nx - 1
=> nx^2 += 2nx - 1
很容易看出这是如何工作的:
1^2 = 0 + 2*1 - 1 = 1
2^2 = 1 + 2*2 - 1 = 4
3^2 = 4 + 2*3 - 1 = 9
4^2 = 9 + 2*4 - 1 = 16
5^2 = 16 + 2*5 - 1 = 25
etc...
因此,在每次迭代中,您只需要保留一些中间变量,因此:
int dx2 = 0, dy2, r2;
for (dx = 1; dx < w; ++dx) { // ignoring bounds checks
dx2 += (dx << 1) - 1;
dy2 = 0;
for (dy = 1; dy < h; ++dy) {
dy2 += (dy << 1) - 1;
r2 = dx2 + dy2;
// do tests here
}
}
intdx2=0,dy2,r2;
对于(dx=1;dx dx2+=(dx好的,听起来很有趣。
我制作了一个C++版本的灵魂,我不知道这是否能帮助你。我认为它的工作速度足够快,因为它几乎在800×600的瞬间。
//(c++ version)
#include<iostream>
#include<cmath>
#include<ctime>
using namespace std;
//ITERATIVE VERSION
//picture witdh&height
#define width 800
#define height 600
//indexex
int i,j;
//initial point coordinates
int x,y;
//variables to work with the array
int p,u;
//minimum dist
double min_dist=2000000000;
//array for memorising the points added
struct point{
int x;
int y;
} points[width*height];
double dist;
bool viz[width][height];
// direction vectors, used for adding adjacent points in the "points" array.
int dx[8]={1,1,0,-1,-1,-1,0,1};
int dy[8]={0,1,1,1,0,-1,-1,-1};
int k,nX,nY;
//we will generate an image with white&black pixels (0&1)
bool image[width-1][height-1];
int main(){
srand(time(0));
//generate the random pic
for(i=1;i<=width-1;i++)
for(j=1;j<=height-1;j++)
if(rand()%10001<=9999) //9999/10000 chances of generating a black pixel
image[i][j]=0;
else image[i][j]=1;
//random coordinates for starting x&y
x=rand()%width;
y=rand()%height;
p=1;u=1;
points[1].x=x;
points[1].y=y;
while(p<=u){
for(k=0;k<=7;k++){
nX=points[p].x+dx[k];
nY=points[p].y+dy[k];
//nX&nY are the coordinates for the next point
//if we haven't added the point yet
//also check if the point is valid
if(nX>0&&nY>0&&nX<width&&nY<height)
if(viz[nX][nY] == 0 ){
//mark it as added
viz[nX][nY]=1;
//add it in the array
u++;
points[u].x=nX;
points[u].y=nY;
//if it's not black
if(image[nX][nY]!=0){
//calculate the distance
dist=(x-nX)*(x-nX) + (y-nY)*(y-nY);
dist=sqrt(dist);
//if the dist is shorter than the minimum, we save it
if(dist<min_dist)
min_dist=dist;
//you could save the coordinates of the point that has
//the minimum distance too, like sX=nX;, sY=nY;
}
}
}
p++;
}
cout<<"Minimum dist:"<<min_dist<<"\n";
return 0;
}
- (SomeBigObjCStruct *)nearestWalkablePoint:(SomeBigObjCStruct)point {
typedef struct _testPoint { // using the IYMapPoint object here is very slow
int x;
int y;
} testPoint;
// see if the point supplied is walkable
testPoint centre;
centre.x = point.x;
centre.y = point.y;
NSMutableData *map = [self getWalkingMapDataForLevelId:point.levelId];
// check point for walkable (case radius = 0)
if(testThePoint(centre.x, centre.y, map) != 0) // bullseye
return point;
// radius is the distance from the location of point. A square is checked on each iteration, radius units from point.
// The point with y=0 or x=0 distance is checked first, i.e. the centre of the side of the square. A cursor variable
// is used to move along the side of the square looking for a walkable point. This proceeds until a walkable point
// is found or the side is exhausted. Sides are checked until radius is exhausted at which point the search fails.
int radius = 1;
BOOL leftWithinMap = YES, rightWithinMap = YES, upWithinMap = YES, downWithinMap = YES;
testPoint leftCentre, upCentre, rightCentre, downCentre;
testPoint leftUp, leftDown, rightUp, rightDown;
testPoint upLeft, upRight, downLeft, downRight;
leftCentre = rightCentre = upCentre = downCentre = centre;
int foundX = -1;
int foundY = -1;
while(radius < 1000) {
// radius increases. move centres outward
if(leftWithinMap == YES) {
leftCentre.x -= 1; // move left
if(leftCentre.x < 0) {
leftWithinMap = NO;
}
}
if(rightWithinMap == YES) {
rightCentre.x += 1; // move right
if(!(rightCentre.x < kIYMapWidth)) {
rightWithinMap = NO;
}
}
if(upWithinMap == YES) {
upCentre.y -= 1; // move up
if(upCentre.y < 0) {
upWithinMap = NO;
}
}
if(downWithinMap == YES) {
downCentre.y += 1; // move down
if(!(downCentre.y < kIYMapHeight)) {
downWithinMap = NO;
}
}
// set up cursor values for checking along the sides of the square
leftUp = leftDown = leftCentre;
leftUp.y -= 1;
leftDown.y += 1;
rightUp = rightDown = rightCentre;
rightUp.y -= 1;
rightDown.y += 1;
upRight = upLeft = upCentre;
upRight.x += 1;
upLeft.x -= 1;
downRight = downLeft = downCentre;
downRight.x += 1;
downLeft.x -= 1;
// check centres
if(testThePoint(leftCentre.x, leftCentre.y, map) != 0) {
foundX = leftCentre.x;
foundY = leftCentre.y;
break;
}
if(testThePoint(rightCentre.x, rightCentre.y, map) != 0) {
foundX = rightCentre.x;
foundY = rightCentre.y;
break;
}
if(testThePoint(upCentre.x, upCentre.y, map) != 0) {
foundX = upCentre.x;
foundY = upCentre.y;
break;
}
if(testThePoint(downCentre.x, downCentre.y, map) != 0) {
foundX = downCentre.x;
foundY = downCentre.y;
break;
}
int i;
for(i = 0; i < radius; i++) {
if(leftWithinMap == YES) {
// LEFT Side - stop short of top/bottom rows because up/down horizontal cursors check that line
// if cursor position is within map
if(i < radius - 1) {
if(leftUp.y > 0) {
// check it
if(testThePoint(leftUp.x, leftUp.y, map) != 0) {
foundX = leftUp.x;
foundY = leftUp.y;
break;
}
leftUp.y -= 1; // moving up
}
if(leftDown.y < kIYMapHeight) {
// check it
if(testThePoint(leftDown.x, leftDown.y, map) != 0) {
foundX = leftDown.x;
foundY = leftDown.y;
break;
}
leftDown.y += 1; // moving down
}
}
}
if(rightWithinMap == YES) {
// RIGHT Side
if(i < radius - 1) {
if(rightUp.y > 0) {
if(testThePoint(rightUp.x, rightUp.y, map) != 0) {
foundX = rightUp.x;
foundY = rightUp.y;
break;
}
rightUp.y -= 1; // moving up
}
if(rightDown.y < kIYMapHeight) {
if(testThePoint(rightDown.x, rightDown.y, map) != 0) {
foundX = rightDown.x;
foundY = rightDown.y;
break;
}
rightDown.y += 1; // moving down
}
}
}
if(upWithinMap == YES) {
// UP Side
if(upRight.x < kIYMapWidth) {
if(testThePoint(upRight.x, upRight.y, map) != 0) {
foundX = upRight.x;
foundY = upRight.y;
break;
}
upRight.x += 1; // moving right
}
if(upLeft.x > 0) {
if(testThePoint(upLeft.x, upLeft.y, map) != 0) {
foundX = upLeft.x;
foundY = upLeft.y;
break;
}
upLeft.y -= 1; // moving left
}
}
if(downWithinMap == YES) {
// DOWN Side
if(downRight.x < kIYMapWidth) {
if(testThePoint(downRight.x, downRight.y, map) != 0) {
foundX = downRight.x;
foundY = downRight.y;
break;
}
downRight.x += 1; // moving right
}
if(downLeft.x > 0) {
if(testThePoint(upLeft.x, upLeft.y, map) != 0) {
foundX = downLeft.x;
foundY = downLeft.y;
break;
}
downLeft.y -= 1; // moving left
}
}
}
if(foundX != -1 && foundY != -1) {
break;
}
radius++;
}
// build the return object
if(foundX != -1 && foundY != -1) {
SomeBigObjCStruct *foundPoint = [SomeBigObjCStruct mapPointWithX:foundX Y:foundY levelId:point.levelId];
foundPoint.z = [self zWithLevelId:point.levelId];
return foundPoint;
}
return nil;